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Generating and Analyzing High-Parameter Histology Images with Histoflow Cytometry
Rajiv W Jain1, David A Elliott2, V Wee Yong3
1Hotchkiss Brain Institute, University of Calgary; Department of Clinical Neurosciences, University of Calgary.
Insights
Histoflow cytometry enhances tissue imaging by enabling high-parameter analysis of immune cells. This method allows detailed profiling and spatial mapping of immune cell subsets within tissues.
Area of Science:
- Immunology
- Microscopy
- Bioinformatics
Background:
- Traditional histology is limited in analyzing immune cell diversity due to constraints on fluorescent parameters.
- Flow cytometry, while powerful for immune cell profiling, dissociates tissues, losing crucial spatial information.
- Existing microscopy techniques struggle to identify complex immune cell subsets requiring multiple protein markers.
Purpose of the Study:
- To develop a method for expanding fluorescent imaging parameters in histology.
- To enable high-parameter, spatially resolved immune cell analysis in tissue sections.
- To bridge the gap between flow cytometry's profiling capabilities and histology's spatial context.
Main Methods:
- Collected spectrally overlapping fluorophore signals and employed spectral unmixing to isolate individual fluorophore signals.
- Developed an analysis pipeline to extract single cells from high-parameter histology images.
- Applied flow cytometry-like gating strategies to profile and map identified immune cell subsets back onto tissue sections.
Main Results:
- Successfully expanded the number of fluorescent parameters detectable in histology images.
- Enabled single-cell level analysis of unique fluorescent properties within tissue sections.
- Quantified immune cell subset abundance and mapped their interactions within the tissue microenvironment.
Conclusions:
- Histoflow cytometry offers a powerful approach to study complex immune populations in histology.
- The method retains spatial information while providing flow cytometry-like immune cell profiling.
- Demonstrated the potential for detailed investigation of immune cell behavior and interactions in situ.
Abstract:
The usage of histology to investigate immune cell diversity in tissue sections such as those derived from the central nervous system (CNS) is critically limited by the number of fluorescent parameters that can be imaged at a single time. Most immune cell subsets have been defined using flow cytometry by using complex combinations of protein markers, often requiring four or more parameters to conclusively identify, which is beyond the capabilities of most conventional microscopes. As flow cytometry dissociates tissues and loses spatial information, there is a need for techniques that can retain spatial information while interrogating the roles of complex cell types. These issues are addressed here by creating a method for expanding the number of fluorescent parameters that can be imaged by collecting the signals of spectrally overlapping fluorophores and using spectral unmixing to separate the signals of each individual fluorophore. These images are then processed using an analysis pipeline to take high-parameter histology images and extract single cells from these images so that the unique fluorescent properties of each cell can be analyzed at a single-cell level. Using flow cytometry-like gating strategies, cells can then be profiled into subsets and mapped back onto the histology sections to not only quantify their abundance, but also establish how they interact with the tissue environment. Overall, the simplicity and potential of using histoflow cytometry to study complex immune populations in histology sections is demonstrated.
